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To run experiments, run the following files in sequence.

  • run function.generate_gp to produce a GP function and save the function values at grid points as function_name.csv. An example of generating a 2D function f1 on 100 grid points over [-5, 5]^2 is given below.
generate_gp(5, 2, 5, 0.5, 'f1')
  • run main.py to execute BPE, B-BPE, B-Fixed-BPE, and GP-UCB.
python main.py [function_name] [beta] [reset_gp]
  • function_name is the name of a generated function (e.g. f1).
  • The supported choices of beta are [2, 6, log], where log represents beta(i) = 3 * log(2i). Please edit the dictionary BETA on the top of main.py to add more choices of beta.
  • reset_gp (0 or 1) represents whether to reset GP posterior at the start of each batch.

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Gaussian Process Bandit Optimization with Few Batches

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